Some Anomalies of Farsighted Strategic Behavior

  • Vittorio Bilò
  • Michele Flammini
  • Gianpiero Monaco
  • Luca Moscardelli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7846)

Abstract

We investigate Subgame Perfect Equilibria, that better capture the rationality of the players in sequential games with respect to other more myopic dynamics like the classical Nash one. We prove that the sequential price of anarchy, that is the worst case ratio between the social performance at a Subgame Perfect Equilibrium and the best possible one, is exactly 3 in cut and consensus games. Moreover, we improve the known Ω(n) lower bound for unrelated scheduling to \(2^{\Omega(\sqrt{n})}\) and refine the corresponding upper bound to 2 n , where n is the number of players. Finally, we determine essentially tight bounds for fair cost sharing games by proving that the sequential price of anarchy is between n + 1 − H n and n. A surprising lower bound of (n + 1)/2 is also determined for the singleton case.

Our results are quite interesting and counterintuitive, as they show that a farsighted behavior generally may lead to a worse performance with respect to myopic one; in fact, Nash equilibria and simple Nash rounds, consisting of a single (myopic) move per player starting from the empty state achieve a price of anarchy which result to be lower or equivalent to the sequential price of anarchy in almost all the considered cases.

Keywords

Nash Equilibrium Subgame Perfect Equilibrium Congestion Game Strong Equilibrium Sequential Game 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aumann, R.J.: Acceptable points in general cooperative n-person games. In: Tucker, A.W., Luce, R.D. (eds.) Contributions to the Theory of Games. Ann. of Math. Stud., vol. 40, pp. 287–324. Princeton University Press, Princeton (1959)Google Scholar
  2. 2.
    Albers, S.: On the Value of Coordination in Network Design. SIAM Journal on Computing 38(6), 2273–2302 (2009)MathSciNetMATHCrossRefGoogle Scholar
  3. 3.
    Albers, S., Lenzner, P.: On Approximate Nash Equilibria in Network Design. In: Saberi, A. (ed.) WINE 2010. LNCS, vol. 6484, pp. 14–25. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Anshelevich, E., Dasgupta, A., Kleinberg, J.M., Tardos, É., Wexler, T., Roughgarden, T.: The Price of Stability for Network Design with Fair Cost Allocation. SIAM Journal on Computing 38(4), 1602–1623 (2008)MathSciNetMATHCrossRefGoogle Scholar
  5. 5.
    Andelman, N., Feldman, M., Mansour, Y.: Strong price of anarchy. In: Proceedings of ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 189–198 (2007)Google Scholar
  6. 6.
    Balcan, M.F.: Leading dynamics to good behavior. SIGecom Exchanges 10, 19–22 (2011)CrossRefGoogle Scholar
  7. 7.
    Bhalgat, A., Chakraborty, T., Khanna, S.: Approximating pure Nash equilibrium in cut, party affiliation, and satisfiability games. In: Proceedings of the 11th ACM Conference on Electronic Commerce (EC), pp. 73–82 (2010)Google Scholar
  8. 8.
    Bilò, V., Fanelli, A., Flammini, M., Melideo, G., Moscardelli, L.: Designing Fast Converging Cost Sharing Methods for Multicast Transmissions. Theory of Computing Systems 47(2), 507–530 (2010)MathSciNetMATHCrossRefGoogle Scholar
  9. 9.
    Bilò, V., Fanelli, A., Flammini, M., Moscardelli, L.: When ignorance helps: Graphical multicast cost sharing games. Theoretical Computer Science 411(3), 660–671 (2010)MathSciNetMATHCrossRefGoogle Scholar
  10. 10.
    Bilò, V., Flammini, M.: Extending the Notion of Rationality of Selfish Agents: Second Order Nash Equilibria. Theoretical Computer Science 412(22), 2296–2311 (2011)MathSciNetMATHCrossRefGoogle Scholar
  11. 11.
    Caragiannis, I., Flammini, M., Kaklamanis, C., Kanellopoulos, P., Moscardelli, L.: Tight Bounds for Selfish and Greedy Load Balancing. Algorithmica 61(3), 606–637 (2011)MathSciNetMATHCrossRefGoogle Scholar
  12. 12.
    Charikar, M., Karloff, H.J., Mathieu, C., Naor, J., Saks, M.E.: Online multicast with egalitarian cost sharing. In: Proceedings of the 20th Annual ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pp. 70–76 (2008)Google Scholar
  13. 13.
    Chekuri, C., Chuzhoy, J., Lewin-Eytan, L., Naor, J., Orda, A.: Non-Cooperative Multicast and Facility Location Games. IEEE Journal on Selected Areas in Communications 25(6), 1193–1206 (2007)CrossRefGoogle Scholar
  14. 14.
    Chien, S., Sinclair, A.: Convergence to approximate nash equilibria in congestion games. In: SODA, pp. 169–178. SIAM (2007)Google Scholar
  15. 15.
    Christodoulou, G., Koutsoupias, E.: The price of anarchy of finite congestion games. In: Proceedings of ACM Symposium on Theory of Computing (STOC), pp. 67–73 (2005)Google Scholar
  16. 16.
    Christodoulou, G., Mirrokni, V.S., Sidiropoulos, A.: Convergence and Approximation in Potential Games. In: Durand, B., Thomas, W. (eds.) STACS 2006. LNCS, vol. 3884, pp. 349–360. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  17. 17.
    Czumaj, A., Krysta, P., Vöcking, B.: Selfish traffic allocation for server farms. In: Proceedings of ACM Symposium on Theory of Computing (STOC), pp. 287–296 (2002)Google Scholar
  18. 18.
    Epstein, A., Feldman, M., Mansour, Y.: Strong equilibrium in cost sharing connection games. In: ACM Conference on Electronic Commerce (EC), pp. 84–92 (2007)Google Scholar
  19. 19.
    Fanelli, A., Flammini, M., Moscardelli, L.: The Speed of Convergence in Congestion Games under Best-Response Dynamics. ACM Transactions on Algorithms 8(3), 25 (2012)MathSciNetCrossRefGoogle Scholar
  20. 20.
    Fanelli, A., Moscardelli, L.: On best response dynamics in weighted congestion games with polynomial delays. Distributed Computing 24(5), 245–254 (2011)MATHCrossRefGoogle Scholar
  21. 21.
    Gourvès, L., Monnot, J.: On Strong Equilibria in the Max Cut Game. In: Leonardi, S. (ed.) WINE 2009. LNCS, vol. 5929, pp. 608–615. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  22. 22.
    Koutsoupias, E., Papadimitriou, C.: Worst-case equilibria. In: Meinel, C., Tison, S. (eds.) STACS 1999. LNCS, vol. 1563, pp. 404–413. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  23. 23.
    Paes Leme, R., Syrgkanis, V., Tardos, É.: The curse of simultaneity. In: Proceedings of Innovations in Theoretical Computer Science (ITCS), pp. 60–67. ACM Press (2012)Google Scholar
  24. 24.
    Paes Leme, R., Syrgkanis, V., Tardos, É.: Sequential Auctions and Externalities. In: SODA, pp. 869–886. ACM (2012)Google Scholar
  25. 25.
    Mirrokni, V.S., Vetta, A.: Convergence issues in competitive games. In: Jansen, K., Khanna, S., Rolim, J.D.P., Ron, D. (eds.) APPROX and RANDOM 2004. LNCS, vol. 3122, pp. 183–194. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  26. 26.
    Nash, J.F.: Equilibrium Points in n-Person Games. Proceedings of the National Academy of Sciences of the United States of America 36, 48–49 (1950)MathSciNetMATHCrossRefGoogle Scholar
  27. 27.
    Nash, J.F.: Non-Cooperative Games. Annals of Mathematics 54(2), 286–295 (1951)MathSciNetMATHCrossRefGoogle Scholar
  28. 28.
    Nisan, N., Roughgarden, T., Tardos, É., Vazirani, V.V.: Algorithmic Game Theory. Cambridge University Press, Cambridge (2007)MATHCrossRefGoogle Scholar
  29. 29.
    Osborne, M.J., Rubinstein, A.: A course in game theory. MIT Press (1994)Google Scholar
  30. 30.
    Roughgarden, T., Tardos, É.: How bad is selfish routing? Journal of the ACM 49(2), 236–259 (2002)MathSciNetCrossRefGoogle Scholar
  31. 31.
    Shapley, L.S.: The value of n-person games. In: Contributions to the Theory of Games, pp. 31–40. Princeton University Press (1953)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Vittorio Bilò
    • 1
  • Michele Flammini
    • 2
  • Gianpiero Monaco
    • 2
  • Luca Moscardelli
    • 3
  1. 1.Dipartimento di Matematica e Fisica “Ennio De Giorgi”Università del SalentoLecceItaly
  2. 2.Dipartimento di Ingegneria e Scienze dell’Informazione e MatematicaUniversità di L’AquilaL’AquilaItaly
  3. 3.Dipartimento di EconomiaUniversità di Chieti-PescaraPescaraItaly

Personalised recommendations